Topic
AI strategy
AI strategy is deciding where AI pays off in an operation and what has to be true before anyone builds. These notes cover readiness: the workflow, the data, the rules and the people, and the signals that say build now or wait.
AI strategy and readinessOctober 8, 2026 · 4 min read
Should your product have an MCP server? A decision guide
Five signals that say build it now, three that say wait, and what a good first server looks like. Written for SaaS and platform teams deciding whether to let ChatGPT, Claude and other agents into their product.
October 8, 2026 · 4 min read
AI readiness for Canadian businesses: a checklist of what has to be true first
Most AI projects fail on the data that was not ready, the workflow nobody mapped, or the guardrail nobody specified until the demo went wrong. The questions we ask in an AI readiness assessment, written as a checklist you can run yourself.
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